Towards a Perceptual Loss: Using a Neural Network Codec Approximation as a Loss for Generative Audio Models
© 2019 Association for Computing Machinery. Generative audio models based on neural networks have led to considerable improvements across fields including speech enhancement, source separation, and text-to-speech synthesis. These systems are typically trained in a supervised fashion using simple ele...
Main Authors: | Ananthabhotla, Ishwarya, Ewert, Sebastian, Paradiso, Joseph A |
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Format: | Article |
Language: | English |
Published: |
Association for Computing Machinery (ACM)
2021
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Online Access: | https://hdl.handle.net/1721.1/137115 |
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